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### OSI Table Definition

Source: https://sidequery.dev

Define an OSI table for orders, specifying dimensions and time dimensions.

```yaml
tables:
  - name: orders
    base_table:
      database: analytics
      schema: public
      table: orders
    dimensions:
      - name: status
        expr: status
        data_type: VARCHAR
    time_dimensions:
      - name: order_date
        expr: created_at
        data_type: TIMESTAMP
    facts:
      - name: revenue
        expr: amount
        default_aggregation: sum
      - name: order_count
        expr: 1
        default_aggregation: sum
```

--------------------------------

### Cube Metric Definition

Source: https://sidequery.dev

Define a Cube metric model, specifying dimensions and measures with their SQL.

```yaml
cubes:
  - name: orders
    sql_table: public.orders
    dimensions:
      - name: status
        sql: status
        type: string
      - name: created_at
        sql: created_at
        type: time
    measures:
      - name: revenue
        sql: amount
        type: sum
      - name: count
        type: count
```

--------------------------------

### Superset Table Definition

Source: https://sidequery.dev

Define a Superset table for orders, specifying columns, metrics, and grouping.

```yaml
table_name: orders
main_dttm_col: created_at
schema: public
columns:
  - column_name: status
    type: VARCHAR
    groupby: true
  - column_name: created_at
    is_dttm: true
metrics:
  - metric_name: total_revenue
    expression: SUM(amount)
  - metric_name: order_count
    expression: COUNT(*)
```

--------------------------------

### Hex Model Definition

Source: https://sidequery.dev

Define a Hex model for the orders table, specifying dimensions and measures.

```yaml
id: orders
base_sql_table: public.orders
dimensions:
  - id: status
    type: string
  - id: created_at
    type: timestamp_tz
measures:
  - id: revenue
    func: sum
    of: amount
  - id: order_count
    func: count
```

--------------------------------

### Sidemantic Model Definition (SQL)

Source: https://sidequery.dev

Define a Sidemantic model using SQL syntax, specifying dimensions and metrics.

```sql
MODEL (
    name orders,
    table public.orders
);

DIMENSION (name status, type categorical);
DIMENSION (name order_date, type time, sql created_at);

METRIC (name revenue, agg sum, sql amount);
METRIC (name order_count, agg count);
```

--------------------------------

### BSL Model Definition

Source: https://sidequery.dev

Define a BSL model for orders, specifying dimensions and measures.

```yaml
orders:
  table: public.orders
  dimensions:
    status:
      expr: _.status
    created_at:
      expr: _.created_at
      is_time_dimension: true
  measures:
    revenue:
      expr: _.revenue
      default_aggregation: sum
```

--------------------------------

### Omni Model Definition

Source: https://sidequery.dev

Define an Omni model for orders, specifying dimensions and measures.

```yaml
name: orders
table_name: orders
schema: public
dimensions:
  status:
    type: string
    sql: ${TABLE}.status
  created_at:
    type: timestamp
    timeframes: [date, week, month]
measures:
  total_revenue:
    aggregate_type: sum
    sql: ${orders.amount}
  count:
    aggregate_type: count
```

--------------------------------

### Count Expression

Source: https://sidequery.dev

Calculates the total count of records. Use this for simple record enumeration.

```yaml
count:
  expr: _.count()
```

--------------------------------

### Sidemantic Model Definition (YML)

Source: https://sidequery.dev

Define a Sidemantic model using YML format, specifying dimensions and metrics with their aggregations and SQL expressions.

```yaml
models:
  - name: orders
    table: public.orders
    dimensions:
      - name: status
        type: categorical
      - name: order_date
        type: time
        sql: created_at
    metrics:
      - name: revenue
        agg: sum
        sql: amount
      - name: order_count
        agg: count
```

--------------------------------

### LookML View Definition

Source: https://sidequery.dev

Define a LookML view for the orders table, including dimensions and measures.

```lookml
view: orders {
  sql_table_name: public.orders ;;

  dimension: status {
    type: string
    sql: ${TABLE}.status ;;
  }
  dimension_group: created {
    type: time
    timeframes: [date, week, month]
    sql: ${TABLE}.created_at ;;
  }
  measure: revenue {
    type: sum
    sql: ${TABLE}.amount ;;
  }
  measure: count {
    type: count
  }
}
```

--------------------------------

### MetricFlow Model Definition

Source: https://sidequery.dev

Define a MetricFlow semantic model, specifying entities, dimensions, and measures with their expressions.

```yaml
semantic_models:
  - name: orders
    model: ref('orders')
    entities:
      - name: order
        type: primary
        expr: order_id
    dimensions:
      - name: status
        type: categorical
      - name: order_date
        type: time
        type_params:
          time_granularity: day
    measures:
      - name: revenue
        agg: sum
        expr: order_amount
      - name: order_count
        agg: count
```

--------------------------------

### Summation Expression

Source: https://sidequery.dev

Calculates the sum of a specified field. Use this for aggregating numerical data.

```yaml
expr: _.amount.sum()
```

--------------------------------

### Sidemantic Model Definition (Python)

Source: https://sidequery.dev

Define a Sidemantic model using Python classes, specifying dimensions and metrics.

```python
from sidemantic import Model, Dimension, Metric

orders = Model(
    name="orders",
    table="public.orders",
    dimensions=[
        Dimension(name="status", type="categorical"),
        Dimension(name="order_date", type="time", sql="created_at"),
    ],
    metrics=[
        Metric(name="revenue", agg="sum", sql="amount"),
        Metric(name="order_count", agg="count"),
    ],
)
```

--------------------------------

### Rill Metrics View Definition

Source: https://sidequery.dev

Define a Rill metrics view for the orders model, specifying time series, dimensions, and measures.

```yaml
type: metrics_view
model: orders
timeseries: created_at
smallest_time_grain: day
dimensions:
  - name: status
    column: status
measures:
  - name: total_revenue
    expression: SUM(amount)
  - name: total_orders
    expression: COUNT(*)
```

--------------------------------

### Snowflake Semantic Model Definition

Source: https://sidequery.dev

Define a Snowflake semantic model for orders analytics, specifying datasets, fields, and metrics.

```yaml
semantic_model:
  - name: orders_analytics
    datasets:
      - name: orders
        source: public.orders
        fields:
          - name: status
            expression:
              dialects:
                - dialect: ANSI_SQL
                  expression: status
    metrics:
      - name: revenue
        expression:
          dialects:
            - dialect: ANSI_SQL
              expression: SUM(orders.amount)
```

--------------------------------

### Malloy Source Definition

Source: https://sidequery.dev

Define a Malloy source for the orders table, specifying primary key, dimensions, and measures.

```malloy
source: orders is duckdb.table('orders') extend {
  primary_key: order_id

  dimension:
    status is status
    order_date is created_at

  measure:
    revenue is sum(amount)
    order_count is count()
}
```
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